Tool for assisting individuals experiencing auditory hallucinations to differentiate between hallucinations and ambient sounds

ABSTRACT

A tool is described for supporting an individual suffering from a mental condition or disorder characterized by auditory hallucination. The tool assists in training the individual to distinguish between an acute auditory hallucinatory episode and ambient sounds. The tool monitors for a deliberate overt activation action by a user, where the activation action represents an indication that the user is hearing sounds. The activation action causes the tool to receive a perception indication from the user. The perception indication is either an indication that the user perceives that they are hearing actual sounds, or an indication that the user perceives that they are experiencing an auditory hallucination. A microphone monitors ambient sounds, which are tested against a threshold to determine and whether the perception indication was correct. A report on the correctness of the perception indications may be provided to the user.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation-in-part of U.S. patent applicationSer. No. 16/109,394 filed on Aug. 22, 2018, the teachings of which arehereby incorporated by reference.

TECHNICAL FIELD

The present technology relates to a tool for assisting individualsexperiencing acute instances of a key symptom of psychotic illness,namely auditory hallucinations, to differentiate between hallucinationsand ambient sounds in the environment.

BACKGROUND

Psychosis broadly and auditory hallucinations specifically are presentin several major mental illnesses, including bipolar disorder,post-traumatic stress disorder (PTSD), and most notably schizophreniaspectrum illnesses. Auditory hallucinations involve hearing voices andother sounds when such sounds are not objectively present.

One objective in treating schizophrenia and other illnesses involvingpsychosis is to provide medication which can obviate the symptoms andallow those suffering with the condition to live in the community.However, because of the complexity of psychosis and the fact thatpsychiatry remains an inexact science, medications are not alwayscompletely effective and can, for a substantial number of sufferers,only partially treat distressing auditory hallucinations or be entirelyineffective in that area.

If a medication regimen is not effective, or if a patient isnon-adherent to the regimen, or if titration or medication adjustment isrequired, symptoms such as hallucinations may remain present, and mayimpede community functioning and quality of life for the patient. At aminimum, this is information that should be brought to the attention ofthe person(s) providing treatment, and the occurrence of acute auditoryhallucinatory episodes may also indicate a serious worsening of thecondition that places the patient and/or others in the community atrisk. However, the nature of psychosis makes it very difficult for apatient to “self diagnose” auditory hallucinations.

SUMMARY

According to the present disclosure, a tool is described for supportingan individual suffering from a mental condition or disordercharacterized by auditory hallucination.

In one aspect, the present disclosure is directed to a method forsupporting an individual suffering from a mental condition or disordercharacterized by auditory hallucination in training the individual indistinguishing between an acute auditory hallucinatory episode andambient sounds. The method comprises monitoring, by at least oneprocessor of a computing device, for a deliberate overt activationaction by a user. The activation action represents an indication thatthe user is hearing sounds, and causes the at least one processor toreceive a perception indication from the user. The perception indicationis either an indication that the user perceives that they are hearingactual sounds, or an indication that the user perceives that they areexperiencing an auditory hallucination. The method then uses at leastone microphone on the computing device to monitor ambient sounds; theseambient sounds are tested against a threshold, and recorded as corrector incorrect. The processor(s) record the perception indication ascorrect where one of the following is true:

-   -   the perception indication is an indication that the user        perceives that they are experiencing an auditory hallucination        and the at least one processor determines that the ambient        sounds fail to satisfy the threshold; or    -   the perception indication is an indication that the user        perceives that they are hearing actual sounds and the at least        one processor determines that the ambient sounds satisfy the        threshold.

The processor(s) record the perception indication as incorrect where oneof the following is true:

-   -   the perception indication is an indication that the user        perceives that they are experiencing an auditory hallucination        and the at least one processor determines that the ambient        sounds satisfy the threshold; or    -   the perception indication is an indication that the user        perceives that they are hearing actual sounds and the at least        one processor determines that the ambient sounds fail to satisfy        the threshold.

In one implementation, the ambient sounds are tested against thethreshold locally on the computing device. In another implementation,the ambient sounds are tested against the threshold remotely bytransmitting the ambient sounds from the computing device to a remotecomputer system and receiving threshold testing results from the remotecomputer system at the computing device.

The processor(s) may further generate a report indicating correctness ofa prior series of perception indications. The report may furthercomprise recommendations for improving discrimination between auditoryhallucinations and ambient sounds, and/or accuracy trends for theperception indications to monitor progress of the user over time.

The perception indication may be subsumed within the activation action.

The threshold may be a minimum confidence level associated with voiceactivity detection of the ambient sounds.

In another aspect, the present disclosure is directed to a computingdevice comprising at least one processor, at least one microphonecoupled to the at least one processor, at least one input device coupledto the at least one processor, and at least one memory coupled to the atleast one processor, the memory containing instructions which, whenexecuted by the at least one processor, cause the at least one processorto implement the above-described method for supporting an individualsuffering from a mental condition or disorder characterized by auditoryhallucination in training the individual in distinguishing between anacute auditory hallucinatory episode and ambient sounds.

In yet another aspect, the present disclosure is directed to a tangiblecomputer-readable medium containing computer-usable instructions forexecution by at least one processor of a computing device, wherein theinstructions, when executed by the at least one processor, cause the atleast one processor to implement the above-described method forsupporting an individual suffering from a mental condition or disordercharacterized by auditory hallucination in training the individual indistinguishing between an acute auditory hallucinatory episode andambient sounds.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other features of the invention will become more apparent fromthe following description in which reference is made to the appendeddrawings wherein:

FIG. 1 shows in schematic form an illustrative system for providing aremote alert signal identifying potential occurrence of an acuteauditory hallucinatory episode and supporting an individual sufferingfrom a mental condition or disorder characterized by auditoryhallucination in training the individual in distinguishing between anacute auditory hallucinatory episode and ambient sounds;

FIG. 2 is a flow chart showing an illustrative method for providing aremote alert signal identifying potential occurrence of an acuteauditory hallucinatory episode;

FIG. 2A is a flow chart showing an illustrative method for supporting anindividual suffering from a mental condition or disorder characterizedby auditory hallucination in training the individual to distinguishbetween an acute auditory hallucinatory episode and ambient sounds;

FIG. 3 shows an illustrative structure for an illustrative function forcapturing the amplitude of audio;

FIG. 4 shows an illustrative structure for an illustrative function forbuilding a sine waveform based on detected amplitude;

FIG. 5 shows an illustrative structure for an illustrative function forapplying detected sound to a waveform;

FIG. 6 shows an illustrative computer system in respect of which aspectsof the present disclosure may be implemented;

FIG. 7 shows an illustrative networked mobile wireless telecommunicationcomputing device in respect of which aspects of the present disclosuremay be implemented; and

FIGS. 8A through 8F show illustrative user interface screens for acomputing device implementing aspects of the methods described herein.

DETAILED DESCRIPTION

Reference is now made to FIG. 1, which shows in schematic form anillustrative system, indicated generally by reference 100, forsupporting an individual suffering from a mental condition or disordercharacterized by auditory hallucination. The system 100 can supporttraining the individual in distinguishing between an acute auditoryhallucinatory episode and ambient sounds, and can provide a remote alertsignal identifying potential occurrence of an acute auditoryhallucinatory episode.

A first networked mobile wireless telecommunication computing device,represented for simplicity of illustration by smartphone 104, isassociated with a user 102 who has been diagnosed with psychosis. Thesmartphone 104 may be owned by the user 102, or merely possessed by theuser 102 under a loan, lease, bailment or other suitable arrangement.The smartphone 104 is merely one representative example of a networkedmobile wireless telecommunication computing device, which may also be atablet, smartwatch or other suitable device possessing a microphone,suitable wireless communication hardware and sufficient processingcapacity. The wireless communication hardware may operate in conjunctionwith other communication hardware, for example a WiFi signal from asmartwatch or tablet may communicate with a router having a wiredconnection to one or more networks.

The processor(s) of the smartphone 104 execute a listening application106, which monitors for a deliberate overt activation action by the user102. Importantly and critically, the activation action represents anaffirmative, unambiguous indication by the user that the user 102 ishearing voices or other sounds. For example, the listening application106 may have a virtual button on a screen thereof that says “I'm hearingthings” or “I am hearing voices” or “Are the voices real?” or“Discretely check the background for noises”, or something similar.Alternatively, the listening application 106 may have an activationaction that involves a specific sequence of button pushes, or a specificgesture, such as vigorously shaking the smartphone 104 in a manner thatcan be unambiguously be detected by an onboard accelerometer. Thelistening application 106 may run in the background for rapid access, ormay be launched when needed. In the latter case, the act of launchingthe listening application 106 may represent an affirmative, unambiguousindication by the user that the user 102 is hearing sounds. Thelistening application 106 may be a stand-alone application, or may be acomponent of a larger software application providing additional featuresand functionality, for example to assist an individual with psychosiswith living in the community.

In some embodiments, as described further below in the context of FIG.2A, the processor(s) executing the listening application 106 on thesmartphone 104 may also receive a perception indication from the user.The perception indication is either an indication that the userperceives that they are hearing actual sounds, or an indication that theuser perceives that they are experiencing an auditory hallucination. Theperception indication may be provided as a separate step, or theperception indication may be subsumed within the activation action. Forexample, with separate steps the overt activation action may be pressingan on-screen button that says “I am hearing sounds” and the perceptionindication may be provided by pressing one of two on-screen buttons,where one button says “I think these are real sounds” and the otherbutton says “I think I am hallucinating”. In a combination there maysimply be the two on-screen buttons that say, respectively, “I thinkthese are real sounds” and “I think I am hallucinating” or words to thateffect; pressing either button necessarily implies an indication thatthe user is hearing sounds such that the perception indication issubsumed within the activation action.

In response to the activation action by the user 102, the processor(s)executing the listening application 106 on the smartphone 104 uses atleast one microphone 108 on the smartphone 104 to monitor ambientsounds, shown as arrows 110. In some embodiments, the microphone 108 maybe inactive prior to the activation action, so that only ambient sounds110 after the activation action are monitored. In other embodiments, theprocessor(s) executing the listening application 106 may cause themicrophone 108 to remain active in the background. For example, theprocessor(s) executing the listening application 106 may continuouslyrecord ambient sounds 110 and store a predetermined duration (e.g. apreceding 5 seconds, 10 seconds, etc.) thereof in a rolling buffer sothat ambient sounds 110 immediately prior to the activation action maybe used, either alone or in addition to ambient sounds 110 following theactivation action.

Optionally, the listening application 106 may display a waveform orother representation of the ambient sounds 110 on a screen of thesmartphone 104.

The processor(s) executing the listening application 106 test theambient sounds 110 against a threshold to determine whether the user 102is experiencing an acute auditory hallucinatory episode. The thresholdis designed to test whether evidence present in the ambient sounds 110supports the perception of the user 102 with respect to actual voices oran auditory hallucination. Depending on the desired bias in terms ofType I error (false positive) vs. Type II error (false negative),various thresholds can be used, alone or in combination. For example,the threshold may be a minimum volume threshold, or may be a minimumconfidence level associated with voice activity detection and/or naturallanguage processing of the ambient sounds 110, e.g. whether or not avoice activity detection/natural language processing engine can identifyspoken works in the ambient sounds 110. These are merely somerepresentative examples of thresholds, and are not intended to belimiting.

The processor(s) executing the listening application 106 may test theambient sounds 110 against the threshold locally on the smartphone 104,or remotely by transmitting the ambient sounds 110 from the networkedmobile wireless telecommunication computing device to a remote computersystem 112 through one or more networks 114 (e.g. comprising one or morewireless networks, intranets, cellular networks, the publically switchedtelephone network (PSTN) and/or the Internet) to which the smartphone104 is coupled and receiving threshold testing results from the remotecomputer system 112 at the smartphone 104. In the latter case, theremote computer system 112 may have far superior processing capacity tothe smartphone 104 so as to more rapidly execute the requiredprocessing, e.g. voice activity detection and/or natural languageprocessing.

If the processor(s) executing the listening application 106 determinethat the ambient sounds 110 fail to satisfy the threshold, thisindicates that the ambient sounds 110 detected by the microphone 108 donot support an inference that the sounds heard by the user 102 areactually present, and therefore that the sounds may be an auditoryhallucination.

Where the processor(s) executing the listening application 106 on thesmartphone 104 also receive a perception indication from the user, theprocessor(s) may also record the perception indication as either corrector incorrect. The processor(s) will record the perception indication ascorrect if (a) the perception indication is an indication that the userperceives that they are experiencing an auditory hallucination and theprocessor(s) determine that the ambient sounds fail to satisfy thethreshold; or (b) the perception indication is an indication that theuser perceives that they are hearing actual sounds and the processor(s)determine that the ambient sounds satisfy the threshold. Theprocessor(s) will record the perception indication as incorrect if (a)the perception indication is an indication that the user perceives thatthey are experiencing an auditory hallucination and the processor(s)determine that the ambient sounds satisfy the threshold; or (b) theperception indication is an indication that the user perceives that theyare hearing actual sounds and the processor(s) determine that theambient sounds fail to satisfy the threshold. Optionally, theprocessor(s) executing the listening application 106 may provide avisual and/or audible notification to the user 102 as to the accuracy ofthe user's perception of whether the user 102 is hearing actual voicesor experiencing an auditory hallucination. This may provide reassuranceto the user 102 that the user 102 is correctly distinguishing betweenactual ambient sounds and auditory hallucination.

After recording the perception indication (where one is received) aseither correct or incorrect, the processor(s) executing the listeningapplication 106 on the smartphone 104 may generate a report, which maybe presented to the user and/or sent to personnel involved in treatingand/or supporting the user 102, such as by transmission to a secondnetworked mobile wireless telecommunication computing device 118associated with a medical professional 120.

As noted above, if the processor(s) executing the listening application106 determine that the ambient sounds 110 fail to satisfy the threshold,this indicates that the ambient sounds 110 detected by the microphone108 do not support an inference that the sounds heard by the user 102are actually present, and therefore that the sounds may be an auditoryhallucination. Accordingly, responsive to the processor(s) executing thelistening application 106 determining that the ambient sounds fail tosatisfy the threshold, the processor(s) executing the listeningapplication 106 may cause the smartphone 104 to wirelessly transmit oneor more alert signals 116 that identify the user 102 and indicate thatthe user 102 may be experiencing an auditory hallucination. Optionally,where the perception indication is correct, i.e. the user 102 hascorrectly perceived that they are experiencing an auditoryhallucination, the processor(s) executing the listening application 106may not send the alert signal(s) 116. Thus, the alert signal(s) 116 maybe sent only where the user experiences an auditory hallucination andincorrectly identifies it as actual sounds. The alert signal(s) 116 aresent, via the network(s) 114, to at least one remote receiving devicebeyond the smartphone 104. Examples of remote receiving devices includeat least one second networked mobile wireless telecommunicationcomputing device 118 associated with a medical professional 120 involvedin treatment of the user 102, a telephone or dispatch system 126associated with an ambulance or paramedic service 128, and a dedicatedmonitoring center 130. The alert signal(s) 116 can be one or more of atext message, a pager message, a telephone call, an e-mail message, apush notification or other types of signal. The alert signal(s) 116 mayindicate that the user 102 may be experiencing an auditory hallucinationeither explicitly, or implicitly (e.g. a push notification on adedicated application running on a smartphone or other device associatedwith a medical professional 120 involved in treatment of the user 102).

The processor(s) may cause transmission of the alert signal 116 inresponse to a single instance for which the processor(s) determines, inresponse to the activation action, that the ambient sounds fail tosatisfy the threshold. In other embodiments, the alert signal(s) 116will only be generated after a predetermined number of instances withina predetermined time period for which, following an activation action bythe user 102, the processor(s) executing the listening application 106determine that the ambient sounds 110 fail to satisfy the threshold.Additionally, in some embodiments, the number of activation actions bythe user, and the number of times that the ambient sounds 110 fail tosatisfy the threshold, may be recorded and transmitted to informclinicians of patient wellness between appointments.

As noted above, the smartphone 104 is merely one representative exampleof a networked mobile wireless telecommunication computing device. Wherethe device (e.g. smartphone 104) has telephone connectivity through thenetwork(s) 114, the alert signal 116 may be, for example, an automatedtelephone call, text message, pager message or e-mail message sentaccording to conventional protocols. Alternatively, the alert signal 116may be transmitted through the network(s) 114 to another system, e.g.remote computer system 112, for further processing. For example, profileinformation 132 about the user 102 may be stored on the remote computersystem 112, and the remote computer system 112 can use the profileinformation 132 to embellish the alert signal 116. For example, thealert signal 116 may consist of a unique identifier for the user 102, ora limited data set (e.g. a unique identifier and timestamp and/orlocation). The remote computer system 112 can forward the embellishedalert signal 116, which can then be forwarded to, for example, one ormore of a device 118 associated with a medical professional 120 involvedin treatment of the user 102, a telephone or dispatch system 126associated with an ambulance or paramedic service 128, and a dedicatedmonitoring center 130. Alternatively or additionally, the remotecomputer system 112 may update an electronic medical record of the user102 based on the alert signal 116. The alert signal 116 may trigger analert within the electronic medical record and/or an alarm on a webportal.

Optionally, where available, the alert signal 116 can include locationinformation (e.g. from a location processor of the smartphone 104). Forexample, if a profile of the user 102 indicates that he or she may posea danger to himself/herself or others in the event of auditoryhallucinations, the alert signal 116 can be used to dispatch emergencymedical personnel 128 to the location of the smartphone 104, which isexpected to be at (or at least near) the location of the user 102. Insuch cases, the alert signal can also provide additional information,such as one or more photographs of the user 102 to assist emergencymedical personnel 128 in identifying the user 102 when they arrive.

Reference is now made to FIG. 2, in which an illustrative method forproviding a remote alert signal identifying potential occurrence of anacute auditory hallucinatory episode is indicated generally at reference200.

At step 202, the method 200 monitors, by at least one processor of afirst computing device, for a deliberate overt activation action by auser. As noted above, the activation action, when detected, representsan indication that the user is hearing sounds. If the activation actionis detected (a “yes” at step 202), the method 200 proceeds to optionalstep 203 to receive a perception indication and then to step 204;otherwise (a “no” at step 202) the method 200 continues to monitor atstep 202.

At step 204, responsive to the activation action being detected, theprocessor(s) using at least one microphone on the first computing deviceto monitor ambient sounds. In one illustrative implementation, theCordova-Plugin-Media sound detector, available from Apache for bothAndroid and iOS platforms at the HTTP URLcordova.apache.org/docs/en/latest/reference/cordova-plugin-media/, maybe used to access the microphone. This package allows the microphone tocapture any ambient sounds around the computing device, and to play,pause and stop recorded audio, change the volume and read the currentposition of playing audio. In one illustrative embodiment, ambientsounds are captured by the interval function (shown below) every 0.4seconds. The amplitude range is 0 to 1, with voice capture sensitivityset to anything more than 0.06 of the amplitude rate to eliminate verylow volume noises. This is merely one illustrative implementation and isnot limiting.

The function for capturing the amplitude of audio in theCordova-Plugin-Media is: media.getCurrentAmplitude(mediaSuccess,[mediaError]). The structure shown at reference 300 in FIG. 3 is used toimplement this function.

Returning to FIG. 2, after step 204 the method 200 proceeds to optionalstep 206, where the processor(s) may display a visual representation ofthe ambient sounds on a display of the first computing device. In oneillustrative implementation, the ambient sounds are visualized as a sinewaveform (other visual representations may also be used). A firstfunction, shown at 400 in FIG. 4, may be used to build the sine waveformbased on detected amplitude. The amplitude is magnified to enableidentification of minor changes in the wave form. The sine curve isdrawn in 10px segments starting at the origin in this function. Theheight of the sine waveform is changing based on detected soundamplitude with a parameter called “unit”. This allows the waveform to beplotted on a display of the first computing device. The detected soundmay then be applied to the waveform using the function shown at 500 inFIG. 5, according to the following recursive steps:

-   -   1. Clear the screen in position (x, y) with context.clearRect;    -   2. Save cleared screen;    -   3. Define color and width of waveform;    -   4. Draw sine curve at moment of t;    -   5. Update moment of t; and    -   6. Return to step (1).

After optional step 206, or from step 204 where optional step 206 isomitted, the method 200 proceeds to step 208, where the processor(s)test the ambient sounds against a threshold. As noted above, this may bedone locally or remotely, and the threshold may be, for example, aminimum volume threshold, a minimum confidence level associated withvoice activity detection and/or natural language processing of theambient sounds, or another suitable threshold.

If the processor(s) determine at step 208 that the ambient soundssatisfy the threshold (a “yes” at step 208), this indicates that theambient sounds detected by the microphone supporting an inference thatthe sounds heard by the user are actually present, and the methodproceeds to optional step 210 to provide a visual and/or audiblenotification to the user, and then returns to step 202.

If the processor(s) determine at step 208 that the ambient sounds failto satisfy the threshold (a “no” at step 208), this indicates that theambient sounds detected by the microphone(s) do not support an inferencethat the sounds heard by the user are actually present, and thereforethat the sounds may be an auditory hallucination. At optional step 209,the method 200 checks whether the perception indication was correct,that is, whether the user 102 perceived that they were experiencing anauditory hallucination. Responsive to the processor(s) determining thatthe ambient sounds fail to satisfy the threshold (a “no” at step 208)and optionally that the user 102 did not correctly perceive that theywere experiencing an auditory hallucination (“actual sounds” at optionalstep 209), the method 200 proceeds to step 212. At step 212, theprocessor(s) transmit an alert signal, via a network to which the firstcomputing device is coupled, to at least one remote receiving devicebeyond the first computing device. The alert signal may be transmitted,for example, in the manner described above. After step 212, the method200 returns to step 202, or may optionally end.

In addition to providing an alert signal if the ambient sounds detectedby the microphone(s) indicate an auditory hallucination, the presentdisclosure also describes methods for supporting an individual inlearning to distinguish between auditory hallucinations and actualambient sounds.

Reference is now made to FIG. 2A, which shows an illustrative method200A for supporting an individual suffering from a mental condition ordisorder characterized by auditory hallucination. The method 200Aprovides support in training the individual to distinguish between anacute auditory hallucinatory episode and ambient sounds, and may be usedin combination with, or separately from, the method 200 shown in FIG. 2,and may be implemented by the listening application 106. The method 200Ais preferably implemented using a networked computing device (e.g. wiredor wireless), and more preferably implemented using a networked mobilewireless telecommunication computing device such as a smartphone, so asto additionally enable the functionality of the method 200 shown in FIG.2. However, the method 200A shown in FIG. 2A is not so limited, and maybe implemented on any suitable microphone-equipped computing device,including a computing device with no network connection (i.e. anisolated or “air gapped” computing device). Moreover, the microphoneneed not be integral to the computing device, but may also be aperipheral microphone that is releasably communicatively coupled to thecomputing device. Thus, references to a microphone being “on” acomputing device should be understood as including a releasableperipheral microphone that is releasably communicatively coupled to thecomputing device.

At step 202A, the method 200 monitors, by at least one processor of afirst computing device, for a deliberate overt activation action by auser. As before, the activation action represents an indication that theuser is hearing sounds.

At step 203A, responsive to the activation action being detected, themethod 200A causes the processor(s) to receive a perception indicationfrom the user. The perception indication received at step 203A is eitheran indication that the user perceives that they are hearing actualsounds, or an indication that the user perceives that they areexperiencing an auditory hallucination. Steps 202A and 203A may bepresented as separate steps as shown, or may be combined into a singlestep in which the perception indication is subsumed within theactivation action. For example, with separate steps the overt activationdetected at step 202A may be pressing an on-screen button that says “Iam hearing sounds” and the perception indication received at step 203Amay be pressing one of two on-screen buttons, where one button says “Ithink these are real sounds” and the other button says “I think I amhallucinating”. In a combination of steps 202A and 203A, there maysimply be the two on-screen buttons that say, respectively, “I thinkthese are real sounds” and “I think I am hallucinating” or words to thateffect; pressing either button necessarily implies an indication thatthe user is hearing sounds such that the perception indication issubsumed within the activation action.

After step 203A, at step 204A the method 200A causes the processor(s) touse at least one microphone on the first computing device to monitorambient sounds. In one illustrative implementation, theCordova-Plugin-Media sound detector, available from Apache for bothAndroid and iOS platforms at the HTTP URLcordova.apache.org/docs/en/latest/reference/cordova-plugin-media/, maybe used to access the microphone, as described above.

Next, at optional step 206A, the processor(s) may display a visualrepresentation of the ambient sounds on a display of the first computingdevice, as described above.

After optional step 206A, or from step 204A where optional step 206A isomitted, the method 200A proceeds to step 208A, where the processor(s)test the ambient sounds against a threshold. As noted above, this may bedone locally on the first computing device or remotely by transmittingthe ambient sounds from the first computing device to a remote computersystem and receiving threshold testing results from the remote computersystem. The threshold may be, for example, a minimum volume threshold, aminimum confidence level associated with voice activity detection and/ornatural language processing of the ambient sounds, or another suitablethreshold. Preferably, in the method 200A the threshold is a minimumconfidence level associated with voice activity detection of the ambientsounds.

Based on the outcome of step 208A, the method 200A causes theprocessor(s) to record the perception indication as either correct orincorrect. The processor(s) will record the perception indication ascorrect (step 218A) if the perception indication is an indication thatthe user perceives that they are experiencing an auditory hallucination(“hallucination” at step 214A) and the processor(s) determine that theambient sounds fail to satisfy the threshold (“no” at step 208A). Theprocessor(s) will also record the perception indication as correct (step218A) if the perception indication is an indication that the userperceives that they are hearing actual sounds (“actual sounds” at step216A) and the processor(s) determine that the ambient sounds satisfy thethreshold (“yes” at step 208A). The processor(s) will record theperception indication as incorrect (step 220A) where the perceptionindication is an indication that the user perceives that they areexperiencing an auditory hallucination (“hallucination” at step 216A)and the processor(s) determine that the ambient sounds satisfy thethreshold (“yes” at step 208A). The processor(s) will record theperception indication as incorrect (step 220A) where the perceptionindication is an indication that the user perceives that they arehearing actual sounds (“actual sounds” at step 214A) and theprocessor(s) determine that the ambient sounds fail to satisfy thethreshold (“no” at step 208A). While FIG. 2A shows step 208A precedingsteps 214A and 216A, in other embodiments the order may be reversedwherein the method may equivalently apply a threshold test dependent onwhether or not the perception indication is an indication that the userperceives that they are hearing actual sounds or an indication that theuser perceives that they are experiencing an auditory hallucination.

After recording the perception indication as either correct (step 218A)or incorrect (step 220A), the method 200A proceeds to step 222A, wherethe processor(s) will generate a report indicating correctness of aprior series of perception indications and present that report to theuser. The series may be a series of one, that is, only the most recentperception indication, or a larger series (e.g. the past two, five, ten,twenty or any arbitrary number of perception indications). The reportgenerated at step 222A may also comprise recommendations for improvingdiscrimination between auditory hallucinations and ambient sounds,accuracy trends for the perception indications to monitor progress ofthe user over time, or both. The recommendations may be based on ananalysis of the types of errors in perception indications. For example,different recommendations may be provided to a user who is more likelyto mistake hallucinations for real sounds than to a user who is morelikely to mistake real sounds for hallucinations. Thus, therecommendations may be tailored based on the user's performance.

Optionally, the report generated at step 222A, or a log indicatingcorrectness of the prior series of perception indications, may betransmitted to one or more healthcare professionals treating orsupporting the user.

After step 222A, the method 200A returns to step 202A or alternativelymay end.

FIGS. 8A through 8F show illustrative user interface screens 800 for anetworked mobile wireless telecommunication computing deviceimplementing aspects of the methods 200, 200A described herein.

FIG. 8A shows an illustrative user interface screen 800 implementing acombination of steps 202A and 203A. There is a box 802 that states “Ithink I am hearing . . . ” with two on-screen buttons 804, 806. Thefirst on-screen button 804 says “a real sound” and the second on-screenbutton 806 says “a hallucination”. Pressing either button necessarilyimplies an indication that the user is hearing sounds; pressing thefirst button 804 is an indication that the user perceives that they arehearing actual sounds and pressing the second button 806 is anindication that the user perceives that they are experiencing anauditory hallucination.

FIGS. 8B and 8C show illustrative user interface screens 800 for steps204A and 206A, respectively. In FIG. 8C, the user interface screen 800displays a waveform 808 representing ambient sounds.

FIGS. 8D and 8E show illustrative user interface screens 800 for steps218A and 220A, respectively. The user interface screen 800 in FIG. 8Dpresents a box 818 indicating that the perception indication wasrecorded as correct at step 218A. Conversely, the user interface screen800 in FIG. 8E presents a box 820 indicating that the perceptionindication was recorded as incorrect at step 220A.

FIG. 8F shows an illustrative user interface screen 800 implementingstep 222A, and presents a box 822 containing the report 824. The report824 includes an indication 826 of the correctness of a prior series ofperception indications, an accuracy trend 828 and recommendations 830for improving discrimination between auditory hallucinations and ambientsounds.

As noted above, in the method 200A the threshold used at step 208A ispreferably a minimum confidence level associated with voice activitydetection of the ambient sounds. The purpose is to identify the presenceof human voices speaking and discriminate between ambient noise andhuman voices, specifically speech. This is referred to as voice activitydetection. The objective is to help the user distinguish between audiohallucinations (voices being heard internally/in their head) andbackground human speech or voices in an adjacent room or area whenanother person present or nearby may not be visible.

Thus, at step 204 or 204A, the method 200, 200A will record a samplingof the ambient sound within a given timeframe. Steps 208, 208A may thenuse computational analysis to determine the presence or absence of humanspeech in the audio sample. In one embodiment, a machine learning modelmay be built using a training set of raw audio signals, which arecaptured from similar environments as would be expected during realworld use and that have been pre-processed and broken down into frames.Features can be engineered from the frames for each data sample with alabelled outcome and used in training a classifier (e.g. support vectormachine, neural net, etc.) that will be able to determine the outcome ofthe sample—being either voiced speech, unvoiced speech, or silence. Themodel can then be tuned and tested on unseen data to evaluate itsperformance level, and then beta tested.

The process of classifying unseen (new) audio data may occur either onthe computing device itself or, in the case of a networked computingdevice, may be transmitted to a cloud based/networked computer foranalysis of the sample. The resulting computational analysis may alsopartially take place onboard (within the computing infrastructure of thenetworked computing device) and externally on another networked device(the cloud). The resulting analysis will calculate the likelihood of thepresence of human speech within the sample.

The process may or may not require a calibration function to initiallyreduce the level of ambient noise and to calculate the thresholds forspeech detection. Such a calibration process would require steps such asreducing the level of ambient noise (commonly done via spectralsubtraction) and then calculating essential features of the sound(specifically the energy thresholds of the audio samples). Theseessential features of the sound can then be classified. (The term“essential” here refers solely to sound features and should not be usedin construing the claims.)

The statistical analysis and classification of energy signals withinaudio files remains the most complex step of voice activity detection,and several subtypes of statistics are commonly used. These include:

-   -   Spectral Slope (based on energy change between different audio        frequencies within audio spectra)    -   Correlation Coefficients    -   Log likelihood ratio    -   Cepstrum: takes inverse Fourier transform of log(spectrum)    -   Modified distance

Several frameworks may be applied to voice activity detection. It is tobe noted that some or all of the frameworks may be subject to copyrightrestrictions, patent restrictions, open source license restrictions orother restrictions, and nothing in this document is to be construed asauthorizing the use of such frameworks without all necessarypermissions. Each of the voice activity frameworks described below isincorporated herein by reference.

One illustrative framework is G.729. Although this is an older algorithmthat has largely been surpassed in performance, it remains a workablesolution and serves as a performance reference point for newer voiceactivity detection protocols. One implementation in MATLAB is availableat the HTTP URL:www.mathworks.com/help/dsp/examples/g-729-voice-activity-detection.html

Another illustrative framework is the WebRCT voice activity detector.This is a Google-developed API primarily for web-based communication,and includes a built-in voice activity detection. While this may not bean ideal approach given the need for local execution, the source code isavailable and could be adapted. An implementation is available at theHTTP URL: pypi.org/project/webrtcvad/.

ETSI VAD is another older algorithm that may be used as a performancestandard (like G.729), and a document that explains aspects ofclassification and noise adjustment is listed at the HTTP URLwww.etsi.org/deliver/etsi_i_ets/300700_300799/300730/01_20_103/ets_300730e01c.pdf.

An illustrative adaptive energy based framework is available at thefollowing HTTP URL:citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.176.6740&rep=rep1&type=pdf.

Neural network based approaches may also be applied to voice activitydetection. One example is found at the HTTP URLieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8278160.

There are also a number of python libraries for manipulating speech,listed under the heading VoiceBook, at the HTTP URLgithub.com/jim-schwoebel/voicebook. There are several Github librariessimilar to VoiceBook, which stretch across different languages. Onecalled SpeechRecognition includes an ambient noise adjustment function,which takes a period during which speech is absent, collects its energythreshold, and subtracts this from the voice recording. It is availableat the HTTP URL:github.com/Uberi/speech_recognition/blob/master/speech_recognition/_init_.py

Other projects listed on GitHub use a variety of techniques todistinguish speech from ambient noise. The simplest applications usespectral subtraction (of the ambient noise pattern from the full audiofile), but some use more complex methods, like trained neural networksand high-level statistics. Most of the raw code made available has beenwritten in python. These include those listed at the following HTTPURLs:

-   -   github.com/eesungkim/Voice_Activity_Detector    -   github.com/jtkim-kaist/VAD    -   github.com/wahibhaq/android-speaker-audioanalysis/tree/master/Android    -   github.com/shriphani/Listener

While certain open source software packages have been described asuseful in implementing certain aspects of the present disclosure, it isto be understood that the present invention, as claimed, is directed notto any single step which may be known in the art, but to an inventivecombination of steps producing a novel and useful result.

Although illustrative embodiments have been described with respect toindividuals who have been diagnosed with psychosis, it will beappreciated that this is merely by way of illustrative example. Thepresent disclosure is not limited to psychosis, and may be applied inrespect of any psychiatric disorder for which auditory hallucinationsare a symptom.

As can be seen from the above description, the technology describedherein represents significantly more than merely using categories toorganize, store and transmit information and organizing informationthrough mathematical correlations. The technology is in fact animprovement to the technology of treatment support for diagnosedpsychiatric conditions. The technology described herein provides a toolfor objective external assessment of a user's progress in improvingtheir ability to discriminate between an actual auditory sensoryexperience or is an occurrence of an acute auditory hallucinatoryepisode, and for notification of relevant third parties. Thisfacilitates the ability of relevant personnel to provide treatment andsupport. As such, the technology is confined to psychiatric monitoringapplications. Moreover, it is to be appreciated that the presenttechnology is not directed to methods of medical treatment or even tomethods of diagnosing a particular disorder; it is applied, inter alia,where a diagnosis has already been made by a human medical practitioner.The technology provides an objective technique for monitoring anindividual's treatment progress within the context of an existingdiagnosis, eliminating subjectivity by either doctor or patient. In thissense, the present technology provides a manually activated mechanicaldiagnostic tool to replace subjective perception with objectivemeasurement. In this sense, the present technology, while innovative inits application and implementation, is analogous in its result to amanually initiated blood tests for (e.g.) triglyceride and cholesterollevels for individuals already diagnosed with cardiovascular disease.Just as the blood tests replaces a subjective assessment of “I have beengetting better at following my diet” with an objective measure of actualprogress that can be relied upon by user and practitioner, the presenttechnology replaces an inherently subjective and unreliable assessmentof the ability to distinguish between perceived and actual sounds with areliable objective assessment.

The present technology may be embodied within a system, a method, acomputer program product or any combination thereof. The computerprogram product may include a computer readable storage medium or mediahaving computer readable program instructions thereon for causing aprocessor to carry out aspects of the present technology. The computerreadable storage medium can be a tangible device that can retain andstore instructions for use by an instruction execution device. Thecomputer readable storage medium may be, for example, but is not limitedto, an electronic storage device, a magnetic storage device, an opticalstorage device, an electromagnetic storage device, a semiconductorstorage device, or any suitable combination of the foregoing.

A non-exhaustive list of more specific examples of the computer readablestorage medium includes the following: a portable computer diskette, ahard disk, a random access memory (RAM), a read-only memory (ROM), anerasable programmable read-only memory (EPROM or Flash memory), a staticrandom access memory (SRAM), a portable compact disc read-only memory(CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk,a mechanically encoded device such as punch-cards or raised structuresin a groove having instructions recorded thereon, and any suitablecombination of the foregoing. A computer readable storage medium, asused herein, is not to be construed as being transitory signals per se,such as radio waves or other freely propagating electromagnetic waves,electromagnetic waves propagating through a waveguide or othertransmission media (e.g., light pulses passing through a fiber-opticcable), or electrical signals transmitted through a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present technology may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language or a conventional procedural programminglanguage. The computer readable program instructions may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider). In some embodiments, electronic circuitry including,for example, programmable logic circuitry, field-programmable gatearrays (FPGA), or programmable logic arrays (PLA) may execute thecomputer readable program instructions by utilizing state information ofthe computer readable program instructions to personalize the electroniccircuitry, in order to implement aspects of the present technology.

Aspects of the present technology have been described above withreference to flowchart illustrations and/or block diagrams of methods,apparatus (systems) and computer program products according to variousembodiments. In this regard, the flowchart and block diagrams in theFigures illustrate the architecture, functionality, and operation ofpossible implementations of systems, methods and computer programproducts according to various embodiments of the present technology. Forinstance, each block in the flowchart or block diagrams may represent amodule, segment, or portion of instructions, which comprises one or moreexecutable instructions for implementing the specified logicalfunction(s). It should also be noted that, in some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the Figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. Some specific examples of the foregoing may havebeen noted above but any such noted examples are not necessarily theonly such examples. It will also be noted that each block of the blockdiagrams and/or flowchart illustration, and combinations of blocks inthe block diagrams and/or flowchart illustration, can be implemented byspecial purpose hardware-based systems that perform the specifiedfunctions or acts, or combinations of special purpose hardware andcomputer instructions.

It also will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer program instructions. These computer readable programinstructions may be provided to a processor of a general purposecomputer, special purpose computer, or other programmable dataprocessing apparatus to produce a machine, such that the instructions,which execute via the processor of the computer or other programmabledata processing apparatus, create means for implementing thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

These computer readable program instructions may also be stored in acomputer readable storage medium that can direct a computer, otherprogrammable data processing apparatus, or other devices to function ina particular manner, such that the instructions stored in the computerreadable storage medium produce an article of manufacture includinginstructions which implement aspects of the functions/acts specified inthe flowchart and/or block diagram block or blocks. The computerreadable program instructions may also be loaded onto a computer, otherprogrammable data processing apparatus, or other devices to cause aseries of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

An illustrative computer system in respect of which aspects of thetechnology herein described may be implemented is presented as a blockdiagram in FIG. 6. For example, the illustrative computer system 600 maybe used to implement the remote computer system 112, as part of adispatch system 126 associated with an ambulance or paramedic service128, and/or part of a dedicated monitoring center 130, all as shown inFIG. 1.

The illustrative computer system is denoted generally by referencenumeral 600 and includes a display 602, input devices in the form ofkeyboard 604A and pointing device 604B, computer 606 and externaldevices 608. While pointing device 604B is depicted as a mouse, it willbe appreciated that other types of pointing device, or a touch screen,may also be used.

The computer 606 may contain one or more processors or microprocessors,such as a central processing unit (CPU) 610. The CPU 610 performsarithmetic calculations and control functions to execute software storedin an internal memory 612, preferably random access memory (RAM) and/orread only memory (ROM), and possibly additional memory 614. Theadditional memory 614 may include, for example, mass memory storage,hard disk drives, optical disk drives (including CD and DVD drives),magnetic disk drives, magnetic tape drives (including LTO, DLT, DAT andDCC), flash drives, program cartridges and cartridge interfaces such asthose found in video game devices, removable memory chips such as EPROMor PROM, emerging storage media, such as holographic storage, or similarstorage media as known in the art. This additional memory 614 may bephysically internal to the computer 606, or external as shown in FIG. 6,or both.

The computer system 600 may also include other similar means forallowing computer programs or other instructions to be loaded. Suchmeans can include, for example, a communications interface 616 whichallows software and data to be transferred between the computer system600 and external systems and networks. Examples of communicationsinterface 616 can include a modem, a network interface such as anEthernet card, a wireless communication interface, or a serial orparallel communications port. Software and data transferred viacommunications interface 616 are in the form of signals which can beelectronic, acoustic, electromagnetic, optical or other signals capableof being received by communications interface 616. Multiple interfaces,of course, can be provided on a single computer system 600.

Input and output to and from the computer 606 is administered by theinput/output (I/O) interface 618. This I/O interface 618 administerscontrol of the display 602, keyboard 604A, external devices 608 andother such components of the computer system 600. The computer 606 alsoincludes a graphical processing unit (GPU) 620. The latter may also beused for computational purposes as an adjunct to, or instead of, the(CPU) 610, for mathematical calculations.

The various components of the computer system 600 are coupled to oneanother either directly or by coupling to suitable buses.

FIG. 7 shows an illustrative networked mobile wireless telecommunicationcomputing device in the form of a smartphone 700. Thus, the smartphone700 is an illustrative representation of the networked mobile wirelesstelecommunication computing device shown as a smartphone 104 in FIG. 1.

The smartphone 700 includes a display 702, an input device in the formof keyboard 704 and an onboard computer system 706. The display 702 maybe a touchscreen display and thereby serve as an additional inputdevice, or as an alternative to the keyboard 704. The onboard computersystem 706 comprises a central processing unit (CPU) 710 having one ormore processors or microprocessors for performing arithmeticcalculations and control functions to execute software stored in aninternal memory 712, preferably random access memory (RAM) and/or readonly memory (ROM) is coupled to additional memory 714 which willtypically comprise flash memory, which may be integrated into thesmartphone 700 or may comprise a removable flash card, or both. Thesmartphone 700 also includes a communications interface 716 which allowssoftware and data to be transferred between the smartphone 700 andexternal systems and networks. The communications interface 716 iscoupled to one or more wireless communication modules 724, which willtypically comprise a wireless radio for connecting to one or more of acellular network, a wireless digital network or a Wi-Fi network. Thecommunications interface 716 will also typically enable a wiredconnection of the smartphone 700 to an external computer system. Amicrophone 726 and speaker 728 are coupled to the onboard computersystem 706 to support the telephone functions managed by the onboardcomputer system 706. Of note, the microphone 726 may be used to detectambient sounds (e.g. ambient sounds 110 as shown in FIG. 1). A locationservices module 722 (e.g. including GPS receiver hardware) may also becoupled to the communications interface 716 to support navigationoperations by the onboard computer system 706. One or more cameras 730(e.g. front-facing and/or rear facing cameras) may also be coupled tothe onboard computer system 706. A magnetometer 732 may also be coupledto the communications interface 716 to support navigation operations bythe onboard computer system 706; the magnetometer functions as anelectronic compass and gathers data used to determine the direction ofmagnetic North. An accelerometer 734 and gyroscope 736 are coupled tothe communications interface 716 to gather data about movement of thesmartphone 700. A light sensor 738 is also coupled to the communicationsinterface 716. Input and output to and from the onboard computer system706 is administered by the input/output (I/O) interface 718, whichadministers control of the display 702, keyboard 704, microphone 726,speaker 728 and camera(s) 730. The onboard computer system 706 may alsoinclude a separate graphical processing unit (GPU) 720. The variouscomponents are coupled to one another either directly or by coupling tosuitable buses.

Without limitation, any one or more of the display 702 (if atouchscreen), keyboard 704, microphone 726, camera 730, accelerometer734 and gyroscope 736 and light sensor 738 may be considered an inputdevice that can be used to monitor for a deliberate overt activationaction by the user.

The term “computer system”, “computing device”, “data processing system”and related terms, as used herein, are not limited to any particulartype of computer system and encompasses servers, desktop computers,laptop computers, networked mobile wireless telecommunication computingdevices such as smartphones, tablet computers, as well as other types ofcomputer systems.

Thus, computer readable program code for implementing aspects of thetechnology described herein may be contained or stored in the memory 712of the onboard computer system 706 of the smartphone 700 or the memory612 of the computer 606, or on a computer usable or computer readablemedium external to the onboard computer system 706 of the smartphone 700or the computer 606, or on any combination thereof.

Finally, the terminology used herein is for the purpose of describingparticular embodiments only and is not intended to be limiting. As usedherein, the singular forms “a”, “an” and “the” are intended to includethe plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”and/or “comprising,” when used in this specification, specify thepresence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, integers, steps, operations, elements,components, and/or groups thereof.

The corresponding structures, materials, acts, and equivalents of allmeans or step plus function elements in the claims below are intended toinclude any structure, material, or act for performing the function incombination with other claimed elements as specifically claimed. Thedescription has been presented for purposes of illustration anddescription, but is not intended to be exhaustive or limited to the formdisclosed. Many modifications and variations will be apparent to thoseof ordinary skill in the art without departing from the scope of theclaims. The embodiment was chosen and described in order to best explainthe principles of the technology and the practical application, and toenable others of ordinary skill in the art to understand the technologyfor various embodiments with various modifications as are suited to theparticular use contemplated.

Certain illustrative embodiments have been described by way of example.It will be apparent to persons skilled in the art that a number ofvariations and modifications can be made without departing from thescope of the invention as defined in the claims. In construing theclaims, it is to be understood that the use of a computing device toimplement the embodiments described herein is essential.

What is claimed is:
 1. A method for supporting an individual sufferingfrom a mental condition or disorder characterized by auditoryhallucination in training the individual in distinguishing between anacute auditory hallucinatory episode and ambient sounds, the methodcomprising: monitoring, by at least one processor of a computing device,for a deliberate overt activation action by a user, wherein theactivation action represents an indication that the user is hearingsounds; wherein the activation action causes the at least one processorto: receive a perception indication from the user, wherein theperception indication is one of: an indication that the user perceivesthat they are hearing actual sounds; and an indication that the userperceives that they are experiencing an auditory hallucination; and useat least one microphone on the computing device to monitor ambientsounds; the at least one processor testing the ambient sounds against athreshold; the at least one processor recording the perceptionindication as correct where one of the following is true: the perceptionindication is an indication that the user perceives that they areexperiencing an auditory hallucination and the at least one processordetermines that the ambient sounds fail to satisfy the threshold; or theperception indication is an indication that the user perceives that theyare hearing actual sounds and the at least one processor determines thatthe ambient sounds satisfy the threshold; the at least one processorrecording the perception indication as incorrect where one of thefollowing is true: the perception indication is an indication that theuser perceives that they are experiencing an auditory hallucination andthe at least one processor determines that the ambient sounds satisfythe threshold; or the perception indication is an indication that theuser perceives that they are hearing actual sounds and the at least oneprocessor determines that the ambient sounds fail to satisfy thethreshold.
 2. The method of claim 1, wherein the at least one processortesting the ambient sounds against the threshold comprises testing theambient sounds against the threshold locally on the computing device. 3.The method of claim 1, wherein the at least one processor testing theambient sounds against the threshold comprises testing the ambientsounds against the threshold remotely by transmitting the ambient soundsfrom the computing device to a remote computer system and receivingthreshold testing results from the remote computer system at thecomputing device.
 4. The method of claim 1, wherein the at least oneprocessor further generates a report indicating correctness of a priorseries of perception indications.
 5. The method of claim 4, wherein thereport further comprises at least one of: (a) recommendations forimproving discrimination between auditory hallucinations and ambientsounds; and (b) accuracy trends for the perception indications tomonitor progress of the user over time.
 6. The method of claim 1,wherein the perception indication is subsumed within the activationaction.
 7. The method of claim 1, wherein the threshold is a minimumconfidence level associated with voice activity detection of the ambientsounds.
 8. A computing device, comprising: at least one processor; atleast one microphone coupled to the at least one processor; at least oneinput device coupled to the at least one processor; at least one memorycoupled to the at least one processor, the memory containinginstructions which, when executed by the at least one processor, causethe at least one processor to implement a method for supporting anindividual suffering from a mental condition or disorder characterizedby auditory hallucination in training the individual in distinguishingbetween an acute auditory hallucinatory episode and ambient sounds, themethod comprising: monitoring, by the at least one processor, for adeliberate overt activation action by a user, wherein the activationaction represents an indication that the user is hearing sounds; whereinthe activation action causes the at least one processor to: receive aperception indication from the user, wherein the perception indicationis one of: an indication that the user perceives that they are hearingactual sounds; and an indication that the user perceives that they areexperiencing an auditory hallucination; and use at least one microphoneon the computing device to monitor ambient sounds; the at least oneprocessor testing the ambient sounds against a threshold; the at leastone processor recording the perception indication as correct where oneof the following is true: the perception indication is an indicationthat the user perceives that they are experiencing an auditoryhallucination and the at least one processor determines that the ambientsounds fail to satisfy the threshold; or the perception indication is anindication that the user perceives that they are hearing actual soundsand the at least one processor determines that the ambient soundssatisfy the threshold; the at least one processor recording theperception indication as incorrect where one of the following is true:the perception indication is an indication that the user perceives thatthey are experiencing an auditory hallucination and the at least oneprocessor determines that the ambient sounds satisfy the threshold; orthe perception indication is an indication that the user perceives thatthey are hearing actual sounds and the at least one processor determinesthat the ambient sounds fail to satisfy the threshold.
 9. The computingdevice of claim 8, wherein the at least one processor testing theambient sounds against the threshold comprises testing the ambientsounds against the threshold locally on the computing device.
 10. Thecomputing device of claim 8, wherein the at least one processor testingthe ambient sounds against the threshold comprises testing the ambientsounds against the threshold remotely by transmitting the ambient soundsfrom the computing device to a remote computer system and receivingthreshold testing results from the remote computer system at thecomputing device.
 11. The computing device of claim 8, wherein the atleast one processor further generates a report indicating correctness ofa prior series of perception indications.
 12. The computing device ofclaim 11, wherein the report further comprises at least one of: (a)recommendations for improving discrimination between auditoryhallucinations and ambient sounds; and (b) accuracy trends for theperception indications to monitor progress of the user over time. 13.The computing device of claim 8, wherein the perception indication issubsumed within the activation action.
 14. The computing device of claim8, wherein the threshold is a minimum confidence level associated withvoice activity detection of the ambient sounds.
 15. A non-transitorycomputer-readable medium containing computer-usable instructions forexecution by at least one processor of a computing device, wherein theinstructions, when executed by the at least one processor, cause the atleast one processor to implement a method for method supporting anindividual suffering from a mental condition or disorder characterizedby auditory hallucination in training the individual in distinguishingbetween an acute auditory hallucinatory episode and ambient sounds, themethod comprising: monitoring, by the at least one processor, for adeliberate overt activation action by a user, wherein the activationaction represents an indication that the user is hearing sounds; whereinthe activation action causes the at least one processor to: receive aperception indication from the user, wherein the perception indicationis one of: an indication that the user perceives that they are hearingactual sounds; and an indication that the user perceives that they areexperiencing an auditory hallucination; and use at least one microphoneon the computing device to monitor ambient sounds; the at least oneprocessor testing the ambient sounds against a threshold; the at leastone processor recording the perception indication as correct where oneof the following is true: the perception indication is an indicationthat the user perceives that they are experiencing an auditoryhallucination and the at least one processor determines that the ambientsounds fail to satisfy the threshold; or the perception indication is anindication that the user perceives that they are hearing actual soundsand the at least one processor determines that the ambient soundssatisfy the threshold; the at least one processor recording theperception indication as incorrect where one of the following is true:the perception indication is an indication that the user perceives thatthey are experiencing an auditory hallucination and the at least oneprocessor determines that the ambient sounds satisfy the threshold; orthe perception indication is an indication that the user perceives thatthey are hearing actual sounds and the at least one processor determinesthat the ambient sounds fail to satisfy the threshold.
 16. Thecomputer-readable medium of claim 15, wherein the instructions cause theat least one processor to test the ambient sounds against the thresholdby testing the ambient sounds against the threshold locally on thecomputing device.
 17. The computer-readable medium of claim 15, whereinthe instructions cause the at least one processor to test the ambientsounds against the threshold by testing the ambient sounds against thethreshold remotely by transmitting the ambient sounds from the computingdevice to a remote computer system and receiving threshold testingresults from the remote computer system at the computing device.
 18. Thecomputer-readable medium of claim 15, wherein the instructions cause theat least one processor to further generate a report indicatingcorrectness of a prior series of perception indications.
 19. Thecomputer-readable medium of claim 18, wherein the report furthercomprises at least one of: (a) recommendations for improvingdiscrimination between auditory hallucinations and ambient sounds; and(b) accuracy trends for the perception indications to monitor progressof the user over time.
 20. The computer-readable medium of claim 15,wherein the perception indication is subsumed within the activationaction.
 21. The computer-readable medium of claim 15, wherein thethreshold is a minimum confidence level associated with voice activitydetection of the ambient sounds.